Fine-grained neural network explanation by identifying input features with predictive information Y Zhang, A Khakzar, Y Li, A Farshad, ST Kim, N Navab Advances in Neural Information Processing Systems 34, 20040-20051, 2021 | 26 | 2021 |
Explaining covid-19 and thoracic pathology model predictions by identifying informative input features A Khakzar, Y Zhang, W Mansour, Y Cai, Y Li, Y Zhang, ST Kim, N Navab Medical Image Computing and Computer Assisted Intervention–MICCAI 2021: 24th …, 2021 | 16 | 2021 |
The stronger the diffusion model, the easier the backdoor: Data poisoning to induce copyright breaches without adjusting finetuning pipeline H Wang, Q Shen, Y Tong, Y Zhang, K Kawaguchi arXiv preprint arXiv:2401.04136, 2024 | 5 | 2024 |
Investigating Copyright Issues of Diffusion Models under Practical Scenarios Y Zhang, TT Tzun, LW Hern, H Wang, K Kawaguchi arXiv preprint arXiv:2311.12803, 2023 | 1 | 2023 |
Analyzing the Effects of Handling Data Imbalance on Learned Features from Medical Images by Looking Into the Models A Khakzar, Y Li, Y Zhang, M Sanisoglu, ST Kim, M Rezaei, B Bischl, ... ICML 2022 Workshop on Interpretable Machine Learning in Healthcare, 2022 | 1 | 2022 |
Enhancing Semantic Fidelity in Text-to-Image Synthesis: Attention Regulation in Diffusion Models Y Zhang, TT Tzun, LW Hern, T Sim, K Kawaguchi arXiv preprint arXiv:2403.06381, 2024 | | 2024 |
AttributionLab: Faithfulness of Feature Attribution Under Controllable Environments Y Zhang, Y Li, H Brown, M Rezaei, B Bischl, P Torr, A Khakzar, ... arXiv preprint arXiv:2310.06514, 2023 | | 2023 |
A Dual-Perspective Approach to Evaluating Feature Attribution Methods Y Li, Y Zhang, K Kawaguchi, A Khakzar, B Bischl, M Rezaei arXiv preprint arXiv:2308.08949, 2023 | | 2023 |